code: def _composite_fully_connected(input_, filter_, bias, act):
      res = tf.raw_ops.MatMul(
          a=input_, b=filter_, transpose_a=False, transpose_b=True
      )
      res = tf.raw_ops.Add(x=res, y=bias)
      if act == "RELU":
          return tf.raw_ops.Relu(features=res)
      elif act == "RELU6":
          return tf.raw_ops.Relu6(features=res)
      elif act == "TANH":
          return tf.raw_ops.Tanh(x=res)
      else:
          return res
  
file_path: tensorflow-upstream/tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
imports: import os
  import sys
  from absl import app
  import tensorflow
  from tensorflow.compiler.mlir.tfr.python import composite
  from tensorflow.compiler.mlir.tfr.python.op_reg_gen import gen_register_op
  from tensorflow.compiler.mlir.tfr.python.tfr_gen import tfr_gen_from_module
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import flags
label_desc: Use image node_id 3 for calling a global function with example usage: _composite_fully_connected(input_, filter_, bias, act) and returns: tf, tf, tf, res